library(assertr)
Warning: package ‘assertr’ was built under R version 4.2.1

candy_2015 <- read_xlsx("raw_data/boing-boing-candy-2015.xlsx") %>%
  clean_names()
candy_2016 <- read_xlsx("raw_data/boing-boing-candy-2016.xlsx") %>%
  clean_names()
candy_2017 <- read_xlsx("raw_data/boing-boing-candy-2017.xlsx") %>%
  clean_names()
New names:

candy_2015
candy_2016
candy_2017
NA
NA
names_2016
  [1] "internal_id"                                                                      "q1_going_out"                                                                    
  [3] "q2_gender"                                                                        "q3_age"                                                                          
  [5] "q4_country"                                                                       "q5_state_province_county_etc"                                                    
  [7] "q6_100_grand_bar"                                                                 "q6_anonymous_brown_globs_that_come_in_black_and_orange_wrappers_a_k_a_mary_janes"
  [9] "q6_any_full_sized_candy_bar"                                                      "q6_black_jacks"                                                                  
 [11] "q6_bonkers_the_candy"                                                             "q6_bonkers_the_board_game"                                                       
 [13] "q6_bottle_caps"                                                                   "q6_boxo_raisins"                                                                 
 [15] "q6_broken_glow_stick"                                                             "q6_butterfinger"                                                                 
 [17] "q6_cadbury_creme_eggs"                                                            "q6_candy_corn"                                                                   
 [19] "q6_candy_that_is_clearly_just_the_stuff_given_out_for_free_at_restaurants"        "q6_caramellos"                                                                   
 [21] "q6_cash_or_other_forms_of_legal_tender"                                           "q6_chardonnay"                                                                   
 [23] "q6_chick_o_sticks_we_don_t_know_what_that_is"                                     "q6_chiclets"                                                                     
 [25] "q6_coffee_crisp"                                                                  "q6_creepy_religious_comics_chick_tracts"                                         
 [27] "q6_dental_paraphenalia"                                                           "q6_dots"                                                                         
 [29] "q6_dove_bars"                                                                     "q6_fuzzy_peaches"                                                                
 [31] "q6_generic_brand_acetaminophen"                                                   "q6_glow_sticks"                                                                  
 [33] "q6_goo_goo_clusters"                                                              "q6_good_n_plenty"                                                                
 [35] "q6_gum_from_baseball_cards"                                                       "q6_gummy_bears_straight_up"                                                      
 [37] "q6_hard_candy"                                                                    "q6_healthy_fruit"                                                                
 [39] "q6_heath_bar"                                                                     "q6_hersheys_dark_chocolate"                                                      
 [41] "q6_hershey_s_milk_chocolate"                                                      "q6_hersheys_kisses"                                                              
 [43] "q6_hugs_actual_physical_hugs"                                                     "q6_jolly_rancher_bad_flavor"                                                     
 [45] "q6_jolly_ranchers_good_flavor"                                                    "q6_joy_joy_mit_iodine"                                                           
 [47] "q6_junior_mints"                                                                  "q6_senior_mints"                                                                 
 [49] "q6_kale_smoothie"                                                                 "q6_kinder_happy_hippo"                                                           
 [51] "q6_kit_kat"                                                                       "q6_laffy_taffy"                                                                  
 [53] "q6_lemon_heads"                                                                   "q6_licorice_not_black"                                                           
 [55] "q6_licorice_yes_black"                                                            "q6_lindt_truffle"                                                                
 [57] "q6_lollipops"                                                                     "q6_mars"                                                                         
 [59] "q6_maynards"                                                                      "q6_mike_and_ike"                                                                 
 [61] "q6_milk_duds"                                                                     "q6_milky_way"                                                                    
 [63] "q6_regular_m_ms"                                                                  "q6_peanut_m_m_s"                                                                 
 [65] "q6_blue_m_ms"                                                                     "q6_red_m_ms"                                                                     
 [67] "q6_green_party_m_ms"                                                              "q6_independent_m_ms"                                                             
 [69] "q6_abstained_from_m_ming"                                                         "q6_minibags_of_chips"                                                            
 [71] "q6_mint_kisses"                                                                   "q6_mint_juleps"                                                                  
 [73] "q6_mr_goodbar"                                                                    "q6_necco_wafers"                                                                 
 [75] "q6_nerds"                                                                         "q6_nestle_crunch"                                                                
 [77] "q6_nown_laters"                                                                   "q6_peeps"                                                                        
 [79] "q6_pencils"                                                                       "q6_pixy_stix"                                                                    
 [81] "q6_real_housewives_of_orange_county_season_9_blue_ray"                            "q6_reese_s_peanut_butter_cups"                                                   
 [83] "q6_reeses_pieces"                                                                 "q6_reggie_jackson_bar"                                                           
 [85] "q6_rolos"                                                                         "q6_sandwich_sized_bags_filled_with_boo_berry_crunch"                             
 [87] "q6_skittles"                                                                      "q6_smarties_american"                                                            
 [89] "q6_smarties_commonwealth"                                                         "q6_snickers"                                                                     
 [91] "q6_sourpatch_kids_i_e_abominations_of_nature"                                     "q6_spotted_dick"                                                                 
 [93] "q6_starburst"                                                                     "q6_sweet_tarts"                                                                  
 [95] "q6_swedish_fish"                                                                  "q6_sweetums_a_friend_to_diabetes"                                                
 [97] "q6_take_5"                                                                        "q6_tic_tacs"                                                                     
 [99] "q6_those_odd_marshmallow_circus_peanut_things"                                    "q6_three_musketeers"                                                             
[101] "q6_tolberone_something_or_other"                                                  "q6_trail_mix"                                                                    
[103] "q6_twix"                                                                          "q6_vials_of_pure_high_fructose_corn_syrup_for_main_lining_into_your_vein"        
[105] "q6_vicodin"                                                                       "q6_whatchamacallit_bars"                                                         
[107] "q6_white_bread"                                                                   "q6_whole_wheat_anything"                                                         
[109] "q6_york_peppermint_patties"                                                       "q7_joy_other"                                                                    
[111] "q8_despair_other"                                                                 "q9_other_comments"                                                               
[113] "q10_dress"                                                                        "x114"                                                                            
[115] "q11_day"                                                                          "q12_media_daily_dish"                                                            
[117] "q12_media_science"                                                                "q12_media_espn"                                                                  
[119] "q12_media_yahoo"                                                                  "click_coordinates_x_y"                                                           

Clean 2015 data


candy_cleaned_2015 <- candy_2015 %>% 
  rename(age = how_old_are_you, 
         going_out = are_you_going_actually_going_trick_or_treating_yourself) %>% 
  mutate(year = str_extract(timestamp, '[0-9]{1,4}'), .after = timestamp) %>%
  mutate(id = row_number(timestamp) + 1e6) %>% 
  mutate(country = NA_character_, .after = age) %>% 
  #mutate(is_going_out = ifelse(is_going_out == "Yes",T, F)) %>% 
  select(id, year:york_peppermint_patties, necco_wafers) %>% 
  # replace all non integer age inputs as NA, convert values to integers
  mutate(age = as.integer(age), year = as.integer(year)) %>% 
  pivot_longer(butterfinger:necco_wafers, names_to = "candy_name", values_to = "rating") %>% 
  select(id, year, going_out, age, country, candy_name, rating)
Warning: NAs introduced by coercionWarning: NAs introduced by coercion to integer range
# maybe pivot_longer for combining three datasets
candy_cleaned_2015

Clean 2016 data


candy_cleaned_2016 <- candy_2016 %>% 
  rename(going_out = are_you_going_actually_going_trick_or_treating_yourself,
         age = how_old_are_you,
         country = which_country_do_you_live_in,
         gender = your_gender) %>%
  mutate(id = row_number(timestamp) + 2e6, .before = timestamp) %>% 
  mutate(year = str_extract(timestamp, '[0-9]{1,4}'), .after = timestamp) %>%
  clean_country_names() %>% 
  select(id, year:york_peppermint_patties, -gender, -which_state_province_county_do_you_live_in) %>% 
  # replace all non integer age inputs as NA, convert values to integers
  mutate(age = as.integer(age), year = as.integer(year)) %>% 
  #pivot_longer(x100_grand_bar:york_peppermint_patties, names_to = "candy_name", values_to = "rating")
  pivot_longer(x100_grand_bar:york_peppermint_patties, names_to = "candy_name", values_to = "rating") %>% 
  select(id, year, going_out, age, country, candy_name, rating)
Warning: NAs introduced by coercionWarning: NAs introduced by coercion to integer range
candy_cleaned_2016
NA

candy_cleaned_2017 <- candy_2017 %>% 
  rename(id = internal_id) %>% 
 # rename(id = internal_id) %>% 
  pivot_longer(q1_going_out:q11_day, names_to = "col_names", values_to = "value") %>%
  select(id, col_names, value) %>%
  mutate(col_names = str_remove(col_names, "q[0-9]_")) %>%
  pivot_wider(names_from = col_names, values_from = value) %>%
  clean_names() %>%
  mutate(year = as.integer(2017), .after = id) %>%
  mutate(age = as.integer(age)) %>% 
  clean_country_names() %>% 
  pivot_longer(x100_grand_bar:york_peppermint_patties, names_to = "candy_name", values_to = "rating") %>% 
  select(id, year, going_out, age, country, candy_name, rating)
Warning: NAs introduced by coercion
candy_cleaned_2017

Summary of countries No cleaning = 118 unique countries Remove non character values = Lowercase = 96 unique countries


clean_country_names <- function(dataframe){
  
us_list <- c("merica", "ahemamerca", "alaska", "america","california","murica",
             "murrika","newjersey","newyork","northcarolina","pittsburgh",
             "trumpistan", "unhingedstates", "uniedstates","unitestates",
             "unitesstates", "uniteds", "us", "theunitedstates",
             "theunitedstatesofamerica", "unitedsates", "unitedstaes",
             "ipretendtobefromcanada,butiamreallyfromtheunitedstates",
             "unitedstate", "unitedstatea", "unitedstated", "usofa", "ussa",
             "ud", "USA", "sub-canadiannorthamericamerica",
             "theyooessofaaayyyyyy", "unitsstates")

uk_list <- c("endland", "england", "scotland", "uk", "unitedkingdom",
             "unitedkindom")

canada_list <- c("can", "canada")

exclude_list <- c("a", "canae", "cascadia", "earth", "fearandloathing",
                  "idontknowanymore", "insanitylately", "namerica", "narnia",
                  "sovietcanuckistan", "subscribetodmuzonyoutube", "denial",
                  "godscountry", "neverland", "oneofthebestones", "seeabove",
                  "somewhere", "eua", "thereisntoneforoldmen",
                  "therepublicofcascadia", "thisone")
  
  dataframe %>%
    mutate(country = str_remove_all(country, "[0-9]*"),
         country = str_to_lower(country),
         country = str_remove_all(country, "[`.' !?0-9]"),
         country = if_else(str_detect(country, "uniteds"),"USA", country),
         country = if_else(str_detect(country, "usa"),"USA", country)) %>% 
    mutate(country = case_when(
      country %in% us_list ~ "USA",
      country %in% uk_list ~ "UK",
      country %in% canada_list ~ "Canada",
      country %in% exclude_list ~ NA_character_,
      !is.na(country) & country != "" ~ "Other"
      ), .after = country)
}

Bind tables together


candy_cleaned_2015 %>% 
  bind_rows(candy_cleaned_2016) %>% 
  bind_rows(candy_cleaned_2017) %>% 
  distinct(candy_name) %>% 
  arrange(candy_name)
NA
candy_cleaned_2015
candy_cleaned_2016
candy_cleaned_2017

Analysis questions What is the total number of candy ratings given across the three years. (Number of candy ratings, not the number of raters. Don’t count missing values) #just a list of all the candy ratings What was the average age of people who are going out trick or treating? # age column What was the average age of people who are not going trick or treating? # age column For each of joy, despair and meh, which candy bar received the most of these ratings? # candy ratings How many people rated Starburst as despair? # starburst column (candy columns)

For the next three questions, count despair as -1, joy as +1, and meh as 0.

What was the most popular candy bar by this rating system for each gender in the dataset ? # candy ratings What was the most popular candy bar in each year? # date or year What was the most popular candy bar by this rating for people in US, Canada, UK, and all other countries? # countries

---
title: "R Notebook"
output: html_notebook
---

```{r}

library(tidyverse)
library(readxl)
library(janitor)
library(here)
library(assertr)


```

```{r}

candy_2015 <- read_xlsx("raw_data/boing-boing-candy-2015.xlsx") %>%
  clean_names()
candy_2016 <- read_xlsx("raw_data/boing-boing-candy-2016.xlsx") %>%
  clean_names()
candy_2017 <- read_xlsx("raw_data/boing-boing-candy-2017.xlsx") %>%
  clean_names()

```

```{r}

candy_2015
candy_2016
candy_2017


```




```{r}

names_2015 <- names(candy_2015)
names_2016 <- names(candy_2016)
names_2017 <- names(candy_2017)

```

### Clean 2015 data

```{r}

candy_cleaned_2015 <- candy_2015 %>% 
  rename(age = how_old_are_you, 
         going_out = are_you_going_actually_going_trick_or_treating_yourself) %>% 
  mutate(year = str_extract(timestamp, '[0-9]{1,4}'), .after = timestamp) %>%
  mutate(id = row_number(timestamp) + 1e6) %>% 
  mutate(country = NA_character_, .after = age) %>% 
  #mutate(is_going_out = ifelse(is_going_out == "Yes",T, F)) %>% 
  select(id, year:york_peppermint_patties, necco_wafers) %>% 
  # replace all non integer age inputs as NA, convert values to integers
  mutate(age = as.integer(age), year = as.integer(year)) %>% 
  pivot_longer(butterfinger:necco_wafers, names_to = "candy_name", values_to = "rating") %>% 
  select(id, year, going_out, age, country, candy_name, rating)


# maybe pivot_longer for combining three datasets
candy_cleaned_2015
```

### Clean 2016 data

```{r}

candy_cleaned_2016 <- candy_2016 %>% 
  rename(going_out = are_you_going_actually_going_trick_or_treating_yourself,
         age = how_old_are_you,
         country = which_country_do_you_live_in,
         gender = your_gender) %>%
  mutate(id = row_number(timestamp) + 2e6, .before = timestamp) %>% 
  mutate(year = str_extract(timestamp, '[0-9]{1,4}'), .after = timestamp) %>%
  clean_country_names() %>% 
  select(id, year:york_peppermint_patties, -gender, -which_state_province_county_do_you_live_in) %>% 
  # replace all non integer age inputs as NA, convert values to integers
  mutate(age = as.integer(age), year = as.integer(year)) %>% 
  #pivot_longer(x100_grand_bar:york_peppermint_patties, names_to = "candy_name", values_to = "rating")
  pivot_longer(x100_grand_bar:york_peppermint_patties, names_to = "candy_name", values_to = "rating") %>% 
  select(id, year, going_out, age, country, candy_name, rating)


candy_cleaned_2016

```

```{r}

candy_cleaned_2017 <- candy_2017 %>% 
  rename(id = internal_id) %>% 
 # rename(id = internal_id) %>% 
  pivot_longer(q1_going_out:q11_day, names_to = "col_names", values_to = "value") %>%
  select(id, col_names, value) %>%
  mutate(col_names = str_remove(col_names, "q[0-9]_")) %>%
  pivot_wider(names_from = col_names, values_from = value) %>%
  clean_names() %>%
  mutate(year = as.integer(2017), .after = id) %>%
  mutate(age = as.integer(age)) %>% 
  clean_country_names() %>% 
  pivot_longer(x100_grand_bar:york_peppermint_patties, names_to = "candy_name", values_to = "rating") %>% 
  select(id, year, going_out, age, country, candy_name, rating)

candy_cleaned_2017
```

Summary of countries
No cleaning = 118 unique countries
Remove non character values = 
Lowercase = 96 unique countries

```{r}

clean_country_names <- function(dataframe){
  
us_list <- c("merica", "ahemamerca", "alaska", "america","california","murica",
             "murrika","newjersey","newyork","northcarolina","pittsburgh",
             "trumpistan", "unhingedstates", "uniedstates","unitestates",
             "unitesstates", "uniteds", "us", "theunitedstates",
             "theunitedstatesofamerica", "unitedsates", "unitedstaes",
             "ipretendtobefromcanada,butiamreallyfromtheunitedstates",
             "unitedstate", "unitedstatea", "unitedstated", "usofa", "ussa",
             "ud", "USA", "sub-canadiannorthamericamerica",
             "theyooessofaaayyyyyy", "unitsstates")

uk_list <- c("endland", "england", "scotland", "uk", "unitedkingdom",
             "unitedkindom")

canada_list <- c("can", "canada")

exclude_list <- c("a", "canae", "cascadia", "earth", "fearandloathing",
                  "idontknowanymore", "insanitylately", "namerica", "narnia",
                  "sovietcanuckistan", "subscribetodmuzonyoutube", "denial",
                  "godscountry", "neverland", "oneofthebestones", "seeabove",
                  "somewhere", "eua", "thereisntoneforoldmen",
                  "therepublicofcascadia", "thisone")
  
  dataframe %>%
    mutate(country = str_remove_all(country, "[0-9]*"),
         country = str_to_lower(country),
         country = str_remove_all(country, "[`.' !?0-9]"),
         country = if_else(str_detect(country, "uniteds"),"USA", country),
         country = if_else(str_detect(country, "usa"),"USA", country)) %>% 
    mutate(country = case_when(
      country %in% us_list ~ "USA",
      country %in% uk_list ~ "UK",
      country %in% canada_list ~ "Canada",
      country %in% exclude_list ~ NA_character_,
      !is.na(country) & country != "" ~ "Other"
      ), .after = country)
}


```

# Bind tables together

```{r}

candy_cleaned_2015 %>% 
  bind_rows(candy_cleaned_2016) %>% 
  bind_rows(candy_cleaned_2017) %>% 
  distinct(candy_name) %>% 
  arrange(candy_name)

```
```{r}
candy_cleaned_2015
candy_cleaned_2016
candy_cleaned_2017
```



Analysis questions
What is the total number of candy ratings given across the three years. (Number of candy ratings, not the number of raters. Don’t count missing values)
#just a list of all the candy ratings
What was the average age of people who are going out trick or treating?
# age column
What was the average age of people who are not going trick or treating?
# age column
For each of joy, despair and meh, which candy bar received the most of these ratings?
# candy ratings
How many people rated Starburst as despair?
# starburst column (candy columns)

For the next three questions, count despair as -1, joy as +1, and meh as 0.

What was the most popular candy bar by this rating system for each gender in the dataset ?
# candy ratings
What was the most popular candy bar in each year?
# date or year
What was the most popular candy bar by this rating for people in US, Canada, UK, and all other countries?
# countries